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Vol 4, 2025
Pages: 1333 - 1344
Review paper
Civil Engineering Editor: Andrija Zorić
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Published: 11.09.2025. Review paper Civil Engineering Editor: Andrija Zorić

OVERVIEW OF ARTIFICIAL NEURAL NETWORKS APPLICATION IN DAMAGE DETECTION OF MASONRY STRUCTURES

By
Bojan Milosevic Orcid logo ,
Bojan Milosevic
Contact Bojan Milosevic

Faculty of Mechanical Engineering and Civil Engineering , University of Kragujevac , Kragujevac , Serbia

Zarko Petrovic Orcid logo ,
Zarko Petrovic

FACULTY OF CIVIL ENGINEERING AND ARCHITECTURE, University of Nis , Niš , Serbia

Nenad Kojic Orcid logo
Nenad Kojic

Department School of Information and Communication Technologies, Academy of technical and art applied studies Belgrade , Beograd , Serbia

Abstract

In order to ensure the durability of masonry structures, prevent their deterioration and serious damage, it is necessary to carry out regular inspections of the condition of building elements. Determining the condition of masonry structures is most often done manually, by visual inspection, which is a time-consuming process, the quality of which largely depends on subjective feeling. As there is an increasing need for automated data processing and work processes today, in recent years there has been an increasing application of artificial intelligence in the process of segmentation and damage detection in masonry structures using artificial neural networks. The aim of this paper is to carry out a detailed analysis of the application of artificial intelligence in the segmentation of masonry elements and the detection of damage to masonry structures through a review and analysis of papers published in the literature.

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